Grad School Projects

Unsupervised Multilingual Event Schema Induction. We outline our novel idea of applying a generative Bayesian model to learn a language-independent event schema representation on different languages, utilizing perspectives brought in by the differences across language, which, however, preserve the semantics.

Audio Event Detection. Restricted Boltzmann Machines were used for unsupervised feature extraction from raw data. The task was to classify the type of event occuring in an input audio clip from a list of pre-defined events. We compared & reported the performance of different classifiers on the classification task.

Netflix Recommendation Challenge. Developed model and memory based collaborative filtering techniques to predict the rating of new movies in the Netflix dataset. Additionally, we also experimented with bipartite clustering as a solution to this problem.